MRI has revolutionized diagnostic imaging over the past two decades. This imaging modality can explore the physical properties of tissue in great detail and is arguably the most powerful imaging technique in the current practice of radiology, especially for imaging of the brain. MRI has become a valuable radiological technique for both structural and functional study of the brain. MRI is also widely used in nearly every aspect of radiological examinations and it is gradually replacing other imaging modalities.
However, MRI does have some limitations. Its constraints are related to the homogeneity of the field generating devices used to form the image. Geometric distortion arising from magnetic field inhomogeneity and gradient field non-linearity has been one of the major concerns. The current generation of MRI scanners has been designed with gradient rise times of less than 200 μs. In order to achieve such short rise times, gradient designers have restricted the length of the gradient coils and also used fewer turns. Such restrictions have led to an increase in the gradient field non-linearity, the result being image distortions. Although slight distortions in MR images normally have little consequences in routine radiological examinations, geometric distortion can be a serious problem in certain MRI applications where high geometric accuracy is required. Examples where precision is a primary consideration include image-guided surgery, and volumetric quantification.
Geometric distortion arising from the static field inhomogeneity and gradient field non-linearity has been studied by using specially designed models, hereafter referred to as “phantoms” to establish control points. Nearly all of these phantoms, however, have been designed for two dimensional (2D) measurements. Two major design approaches have been employed, one using square grids, and the other using cylindrical rods or capillary tubes. A common feature in both design approaches is that the control points are defined only through the intersection of the imaging slice with the grids or cylindrical rods. A clear limitation in these approaches is that only the two coordinates of the each control point's location in the imaging plane can be measured. The third coordinate (that is perpendicular to the imaging plane) is immeasurable and is unknown. Therefore, the measurement of geometric distortion with 2D phantoms only provides an incomplete description of the image distortion. In addition to this serious limitation, mapping geometric distortion in the entire imaging volume using 2D phantoms is time consuming. It often requires measurements with the phantom positioned at different locations and with different orientations. Additional errors can easily be introduced in the process of repositioning.
For a complete mapping of geometric distortion in MRI, control points defined in 3D are required. One previous study [1,2] which used control points defined in 3D to study geometric distortion used spheres of a certain size arranged in three dimensions. In order to specify the positions of the control points, the centre of the gravity of the spheres was used to generate the control points' positions. To ensure accuracy, such an approach requires the spheres to have a sufficient size. This requirement puts a limit on the number of spheres that can be arranged in a phantom. In the earlier study, spheres of 11 mm in diameter were used, and two phantoms were constructed that contained 427 and 793 control points, respectively. The accuracy associated with the positional measurement of the control points appeared to be dependent on a number of factors including the size of the image voxels.
This approach of using “point-like” objects, i.e. spheres, to define a point in space therefore has limitations, particularly on the number of control points that can be introduced.
There are two main requirements for comprehensive and accurate mapping of geometric distortion in 3D. First, the number of sampling points (control points) needs to be large enough to provide a comprehensive mapping of the spatial variations of the distortion. Dense sampling is necessary if detailed spatial information on local deformations is to be obtained. Secondly, the positions of the sampling or control points must be measured with accuracy, as this accuracy ultimately determines the spatial quantification of the geometric distortion.
It is an aim of this invention to provide an improved method and apparatus for mapping geometric distortion in imaging applications, such as MRI. The mapped distortion can then be used to correct acquired images.